Algotale (Wildnet)
Senior Data Engineer / Data Scientist
RemoteIndia only
- Role
- Data Engineering
- Experience
- Senior
- Employment
- Full-time
Salary not disclosed
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No BS summary
Senior Data Engineer/Scientist with 3-5 years of experience in Python, ETL, statistical analysis, and data optimization. Must be comfortable with large datasets, building pipelines, and deriving insights. Requires strong SQL skills.
Core skills
PythonETLSQL
Required skills
statistical analysisdata optimization
Optional skills
SASSAS programmingSAS data processingSAS analyticsAWSAzureGCPdata visualization
Senior Data Engineer / Data Scientist
Experience: 3–5 Years Job Type: Full-Time
Job Summary
We are looking for a skilled Senior Data Engineer / Data Scientist with 3–5 years of hands-on experience in Python, ETL pipeline development, statistical analysis, and data optimization. The ideal candidate should be comfortable working with large datasets, building reliable data pipelines, performing statistical analysis, and translating data into meaningful insights.
Key Responsibilities
- Design, develop, and maintain robust and scalable ETL pipelines for data extraction, transformation, and loading.
- Develop efficient data processing and transformation workflows using Python.
- Perform statistical analysis on structured and unstructured datasets to identify trends, patterns, and business insights.
- Optimize data pipelines, queries, and data processing workflows for improved performance and scalability.
- Clean, validate, transform, and prepare data for analytics and reporting.
- Work with cross-functional teams to understand data requirements and deliver reliable data solutions.
- Identify data quality issues and implement appropriate validation and cleansing processes.
- Develop reusable and maintainable Python scripts and data processing solutions.
- Troubleshoot pipeline failures and resolve data-related issues.
- Document data workflows, pipelines, processes, and technical solutions.
- Ensure data solutions follow best practices for performance, reliability, and maintainability.
Required Skills & Experience
- 3–5 years of relevant experience in Data Engineering, Data Science, Analytics Engineering, or a similar role.
- Strong hands-on experience with Python.
- Strong experience in ETL pipeline development and data transformation.
- Solid understanding of statistical analysis and statistical concepts.
- Experience with data optimization, including query and pipeline performance optimization.
- Strong SQL skills and experience working with relational databases.
- Experience working with large datasets and data processing workflows.
- Strong analytical and problem-solving skills.
- Ability to work independently as well as collaborate effectively with technical and business teams.
Preferred Skills
- SAS experience is highly preferred.
- Experience with SAS programming, SAS data processing, or SAS analytics.
- Exposure to cloud data platforms such as AWS, Azure, or GCP.
- Experience with data visualization and reporting tools.
- Knowledge of data warehousing and database concepts.
- Familiarity with modern data engineering tools and frameworks.
What you'll do
- Design, develop, and maintain robust and scalable ETL pipelines for data extraction, transformation, and loading.
- Develop efficient data processing and transformation workflows using Python.
- Perform statistical analysis on structured and unstructured datasets to identify trends, patterns, and business insights.
- Optimize data pipelines, queries, and data processing workflows for improved performance and scalability.
- Clean, validate, transform, and prepare data for analytics and reporting.
- Work with cross-functional teams to understand data requirements and deliver reliable data solutions.
- Identify data quality issues and implement appropriate validation and cleansing processes.
- Develop reusable and maintainable Python scripts and data processing solutions.
- Troubleshoot pipeline failures and resolve data-related issues.
- Document data workflows, pipelines, processes, and technical solutions.
- Ensure data solutions follow best practices for performance, reliability, and maintainability.
What they require
- 3–5 years of relevant experience in Data Engineering, Data Science, Analytics Engineering, or a similar role.
- Strong hands-on experience with Python.
- Strong experience in ETL pipeline development and data transformation.
- Solid understanding of statistical analysis and statistical concepts.
- Experience with data optimization, including query and pipeline performance optimization.
- Strong SQL skills and experience working with relational databases.
- Experience working with large datasets and data processing workflows.
- Strong analytical and problem-solving skills.
- Ability to work independently as well as collaborate effectively with technical and business teams.
Unknown
Salary not disclosed